Trend on the Implementation of Analytical Techniques for Big Data in Construction Research (2000-2014)

被引:0
|
作者
Omran, Behzad Abounia [1 ]
Chen, Qian [1 ]
机构
[1] Ohio State Univ, Construct Syst Management, 590 Woody Hayes Dr, Columbus, OH 43210 USA
来源
CONSTRUCTION RESEARCH CONGRESS 2016: OLD AND NEW CONSTRUCTION TECHNOLOGIES CONVERGE IN HISTORIC SAN JUAN | 2016年
关键词
Big data; Construction; Analytical techniques;
D O I
暂无
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In recent years, the digital world has experienced an explosion in the magnitude of data being captured and recorded in various industry fields. Accordingly, big data management has emerged to analyze and extract value out of the collected data. The traditional construction industry also experiences an increase in data generation and storage. However, its potential and ability for adopting big data techniques has not been adequately studied. This paper investigates the trends of utilizing big data techniques in the construction research community, which eventually will impact construction practice. The application of 26 popular big data analysis techniques in six different construction research areas (represented by 30 prestigious construction journals) was thoroughly reviewed. The results show that many of these techniques have already been used by researchers in this field although the frequencies of using each technique in construction research as well as individual research areas varied. Also, differences were identified between the overall trends of using big data techniques in construction research versus their use in all engineering research fields. While showing a great potential of applying big data techniques in studying construction-related issues, this research also identified existing gaps for the research community to fill in its future endeavor.
引用
收藏
页码:990 / 999
页数:10
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